The increasing amount of XML datasets available to casual users increases the necessity of investigating techniques to extract knowledge from these data. Data mining is widely applied in the database research area in order to extract frequent correlations of values from both structured and semi structured datasets. Extracting information from semi structured documents is a very hard task, and is going to become more and more critical as the amount of digital information available on the Internet grows. Indeed, documents are often so large that the data set returned as answer to a query may be too big to convey interpretable knowledge. Here we describe the an approach to mine the data using Tree-based association rules from XML documents. Thus the rules provide information on both the structure and the content of XML documents. Moreover, they can be stored in XML format to be queried later on. The mined knowledge is approximate, intensional knowledge used to provide the quick, approximate answers to queries and also the information about structural regularities that can be used as data guides for document querying. Association analysis which is useful for discovering interesting relationship hidden in the datasets. The application of data mining techniques to extract useful knowledge from XML datasets has received a lot of attention in the recent years due to the wide availability of these datasets.